1. Field of the Invention
This invention relates to a signal encoding device for low-bit encoding of voice signals or the like by vector quantization.
2. Description of the Prior Art
Among methods of low-bit encoding voice signals for transmission or recording and high-quality reconstruction of the voice signals, the partial auto-correlation (PARCOR) method which uses feature parameters extracted by linear prediction analysis, and the code excited linear prediction (CELP) method with improved voice quality are known to be excellent. However, these methods require complicated processes for encoding and reconstructing voice signals, and especially in the CELP method, a large-capacity memory is required for a code book used for vector quantization of residual waveforms, thus making the hardware expensive to construct.
Accordingly, in cases where a simple hardware configuration is demanded in preference to the voice reproduction quality, for example, in electronic apparatus for producing simple voice messages or voice guidance, the vector pulse code modulation (VPCM) method has heretofore been used in which the original waveform of a voice signal is vector-quantized using a low-bit code book. In the VPCM method, as shown in FIG. 14, an analog-to-digital converted voice signal is first divided into blocks of N samples (where N is an integer not smaller than 2), and each divided voice signal is sequentially compared with a plurality of patterns using a distance calculating circuit 101. The plurality of patterns are each composed of N samples of data each comprising the same number of bits as that of the quantization bits of the voice signal. A variety of these patterns (e.g., 256 kinds of patterns addressable by eight bits at minimum) are stored in a code book 102 in a memory. The 256 kinds of patterns are selected beforehand, based on the actual voice data to be encoded, using an appropriate method so as to minimize the quantization error. The patterns stored in the code book 102 are read out one by one by a pattern selector 103 and sequentially compared with each divided voice signal. The pattern that provides the smallest deviation (distance) from the voice signal is identified by a minimum value identifying circuit 104, and the address of that pattern in the code book 102 is output as coded data. This means that a voice signal represented by N samples is converted to address data in the code book 102 (i.e. the address of the pattern closest to the voice signal). In the case of 8-bit quantization, for example, data consisting of eight samples of the voice signal (i.e. a total of 64 bits) is compressed to 8-bit address data. Reconstruction from the data encoded by the VPCM method is achieved by sequentially reading out the patterns from the same code book by the addresses of the coded data and converting the data from digital to analog form.
However, the VPCM method has a problem in that the memory capacity required is still too large, if not so large as in the CELP method, to make the hardware simple enough. In the above example, the size of the code book 102 is required to be 16-kilobits (8 bits.times.8 samples.times.256 patterns) to store a plurality of patterns. Furthermore, the optimum patterns stored in the code book 102 are dependent on the actual voice data used in all kinds of apparatus mentioned above. As a result, when the voice data are changed, the patterns must be reselected to match the new voice data. This impairs the versatility of the ROM that constitutes the code book 102, and thus prevents the reduction of costs by mass production.